1. Field of the Invention
The present invention relates to a method for coding a ring-shaped element of a digital image. More specifically, the present invention relates to a method for coding such an element in which the “useful” information is ring-shaped or circular, that is, where the information to be coded varies according to the angular position in concentric circles.
2. Discussion of the Related Art
An example of application of the present invention is the coding of the iris of an eye in a digital image in a recognition process. On the one hand, the iris of an eye is a ring-shaped element delimited by the cornea and by the pupil. On the other hand, an iris is characterized by its texture, which is a set of three-dimensional patterns of bumps and holes, each pattern having in the iris a radial direction. Such a texture translates, upon digital two-dimensional acquisition, as the alternation of light and dark areas. The texture variation in the iris from the pupil edge to the cornea along a radial direction is very small. The information characteristic of the iris texture varies according to the angular position on concentric circles.
To enable relatively fast iris recognition, rather than comparing point by point a processed image with reference images, various methods for extracting its texture have been provided.
A first known method consists, as discussed in U.S. Pat No. 5,572,596 and in international patent application 00/62239, both of which are incorporated herein by reference, of decomposing the texture of the digital image into wavelets. In practice, this decomposition in wavelets or sub-strips is implemented by means of filtering cells applied on the space coordinates of the image and chosen to isolate low frequencies from high frequencies. After each filtering, a decimation (or sub-sampling by two) is performed, thus limiting the calculation complexity without losing information. However, this type of sub-strip coding imposes use of a large memory storage to keep the significant information of the texture of the digital image.
FIG. 1 schematically illustrates, in the form of a block diagram, another known method for coding an iris, which consists of performing a local spectral decomposition by a set of band-pass filters, generally Gabor filters.
A digital image of an eye IMAGE, in which the iris to be coded has previously been localized, is considered. First, at block 101 (CONVERSION), the general ring-shape of the iris is transformed in straight rectangular form. This is done by converting the Cartesian coordinates of the iris into polar coordinates, by means of a constant angle polar conversion.
FIG. 2A schematically illustrates an iridian ring 201, delimited by a pupillary circle P and by the circular limit I between the iris and the cornea. An intermediary circle C between limits I and P is considered. Circle C includes the information to be coded.
By conversion 101, iridian ring 201 is transformed into a rectangular image 202 illustrated in FIG. 2B, in which the data of circle C are now distributed on a line, for example, horizontal.
At the next step, at block 102 (GABOR), a number of lines of the image and a number of points in these lines is selected and a filtering is applied to the retained discrete values, generally the pixel intensity (levels of grey), by means of a Gabor filter (band-pass). The choice of the central frequencies of the strips and of the bandwidths is performed according to a compromise between the constraints of precision and significance of the information extracted from the filtering. Generally, to obtain reliable results, the points of each of the selected lines are filtered over three frequency fields. “Frequency” here means a relative frequency expressed in cycles per image, that is, which refers to the dimensions of the initial image. The extracted information thus does not depend on the digitizing conditions, which enables subsequent direct comparison between a processed image and a reference image.
The used Gabor filter is a complex filter. For each of the central frequencies of the filer, analog information as to the real and imaginary parts Re and Im of the filtering products is thus obtained after filtering. The D.C. component being eliminated by the filtering, the obtained information varies around the used reference. FIGS. 2C and 2D respectively illustrate an example of variation of real part Re and of imaginary part Im along time t on a portion of a line of the image.
At the next step 103 (BINAR), illustrated in FIGS. 2E and 2F, the preceding data Re and Im are transformed into binary data.
Then, at block 104 (CODING), the binary data are coded, taking the phase into account (the information being in the angular direction). The phase coding is possible due to the fact that the Gabor filter is a complex filter and that the real and imaginary portions of the filter are in quadrature. Indeed, this enables considering that the ratio of the real and imaginary parts Re and Im is equal to the tangent of the phase.
The codes thus obtained for each of the processed lines or points are then used for any appropriate processing, for example, a comparison with reference codes to enable an iris recognition. An example of a known method for coding the local phase is described in U.S. Pat. No. 5,291,560, which is incorporated herein by reference.
A disadvantage of a Gabor filter method is the fact that it requires many calculations during the filtering, due to the very nature of the used filters. Indeed, the size of the convolution cores with respect to the size of the image to be convoluted (even after the gaussian envelope characteristic of Gabor filters has been truncated) and the complex structure including a real part and an imaginary part, of the filters lengthen the calculation times.
Another disadvantage is that the accuracy of the obtained coding is directly linked to the number of calculations. Accordingly, if more information is desired to discriminate two images, the amount and time of calculation must be increased.